Multi i-TED characterization

Fourth: Per pixel threshold

• In the previous notebook it was proposed to apply thresholds per pixel:
  • To get to a lower overall threshold that should equate to better resolution.
  • To decrease the size of files, which increases greatly for lower threshoilds due to noise.
  • To study if it impacts the considerable increase in resolution present in iTED-C-0 that was hypothesised being related to noise starting the integration window.
• The 888 configuration is compared to 887 and 88c which stands for 887 with some pixels changed manually.
• Studies of alpha activity and noise are added.

pkg_ver = lambda pkg: "{:<20}{:}".format(pkg.__name__,pkg.__version__)

# ROOT
import uproot
print(pkg_ver(uproot))
import ROOT

# Machine Learning
import sklearn
print(pkg_ver(sklearn))
import torch
print(pkg_ver(torch))

# Data science
import scipy
print(pkg_ver(scipy))
import numpy
print(pkg_ver(numpy))
import pandas
print(pkg_ver(pandas))

# Visualizations
import matplotlib
print(pkg_ver(matplotlib))
import matplotlib.pyplot as plt

import tqdm
print(pkg_ver(tqdm))

uproot              4.3.5
Welcome to JupyROOT 6.26/10
sklearn             1.2.2
torch               2.0.0rc5
scipy               1.10.1
numpy               1.24.2
pandas              1.5.3
matplotlib          3.6.3
tqdm                4.62.3

%jsroot

class spectrum:
    
    def __init__(self, TH1D_, iTED_, Crystal_, Configuration_, Window_, Calibration_):  

        self.__TH1D = TH1D_
        self.__iTED = iTED_
        self.__Crystal = Crystal_
        self.__Configuration = Configuration_
        self.__Window = Window_
        self.__Calibration = Calibration_
        
    def __call__(self, ch):
        return numpy.polyval(self.__Calibration[::-1],ch)
    
    def __ch__(self, en):
        p = numpy.poly1d(self.__Calibration[::-1])
        temp  = set(i for i in (p - en).roots if i > 0)
        return list(temp).pop()
    
    def TH1D(self):
        return self.__TH1D
    
    def Calibration(self):
        return self.__Calibration
    
    def iTED(self):
        return self.__iTED
    
    def Crystal(self):
        return self.__Crystal
    
    def Configuration(self):
        return self.__Configuration
    
    def Window(self):
        return self.__Window
    
    def Noise(self, Time_):
        return self.__TH1D.Integral(
            0,
            self.__TH1D.FindBin(self.__ch__(200))
        )/Time_
    
    def Alpha(self, Time_):
        return self.__TH1D.Integral(
            self.__TH1D.FindBin(self.__ch__(1600)),
            self.__TH1D.FindBin(self.__ch__(2800))
        )/Time_
    
    def __repr__(self):
        return "iTED: {},Crystal: {},Configuration: {},Window: {}".format(
            self.__iTED,
            self.__Crystal,
            self.__Configuration,
            self.__Window
        )
    
    def __str__(self):
        return "{}.{}.{}.{}".format(
            self.__iTED,
            self.__Crystal,
            self.__Configuration,
            self.__Window
        )

iTEDA_cal = pandas.read_csv(
    "../../data/2023-03-02/Energy_Calibrations_02_03_2023/Energy_Calibrations_iTEDA.dat",
    delim_whitespace=True,
    names=["P0","P1","P2"]
)

iTEDB_cal = pandas.read_csv(
    "../../data/2023-03-02/Energy_Calibrations_02_03_2023/Energy_Calibrations_iTEDB.dat",
    delim_whitespace=True,
    names=["P0","P1","P2"]
)

iTEDC_cal = pandas.read_csv(
    "../../data/2023-03-02/Energy_Calibrations_02_03_2023/Energy_Calibrations_iTEDC.dat",
    delim_whitespace=True,
    names=["P0","P1","P2"]
)

iTEDD_cal = pandas.read_csv(
    "../../data/2023-03-02/Energy_Calibrations_02_03_2023/Energy_Calibrations_iTEDD.dat",
    delim_whitespace=True,
    names=["P0","P1","P2"]
)

iTED_cal = pandas.concat([iTEDA_cal.T, iTEDB_cal.T, iTEDC_cal.T, iTEDD_cal.T], axis=1, keys=['A', 'B', 'C', 'D'])

iTED_cal

	A					B					C					D
	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4
P0	97.91440	138.744000	164.131000	96.575700	184.627000	123.545000	181.753000	164.939000	162.539000	156.664000	115.328000	147.053000	129.204000	144.779000	132.346000	91.325100	138.429000	121.824000	138.067000	122.738000
P1	1.96942	1.813160	2.304510	1.764130	2.327000	2.228220	2.581200	2.116580	2.010630	2.193700	2.179250	2.005310	2.079170	2.152760	2.311890	2.016440	2.065850	2.071090	2.132460	1.964320
P2	0.00042	0.000665	0.001125	0.000595	0.001193	0.000559	0.001048	0.001154	0.000915	0.000946	0.000469	0.000859	0.000717	0.000836	0.000898	0.000479	0.000809	0.000667	0.000949	0.000705

config = ["888", "887", "88c"]
CW = [100,150,200,250]

ited = ["A","B","C","D"]
crystal = [0,1,2,3,4]

midx = pandas.MultiIndex.from_product(
    [config, CW],
    names=['Configuration', 'Window']
)

mcol = pandas.MultiIndex.from_product(
    [ited, crystal],
    names=['iTED', 'Crystal']
) 

spectra = pandas.DataFrame(index = midx, columns = mcol)

# Access using spectra[iTED,Crystal][Configuration,Window]

iTEDA = {
    "888-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_02_23_T.13_40_46_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW100.root","READ"),
    "888-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_02_23_T.13_40_46_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW150.root","READ"),
    "888-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_02_23_T.13_40_46_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW200.root","READ"),
    "888-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_02_23_T.13_40_46_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW250.root","READ"),
    "88c-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDA-A2_D.2023_03_14_T.14_28_07_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "88c-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDA-A2_D.2023_03_14_T.14_28_07_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "88c-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDA-A2_D.2023_03_14_T.14_28_07_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "88c-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDA-A2_D.2023_03_14_T.14_28_07_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW250.root","READ"),
    "887-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_03_21_T.14_50_48_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "887-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_03_21_T.14_50_48_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "887-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_03_21_T.14_50_48_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "887-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDA-A2_D.2023_03_21_T.14_50_48_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW250.root","READ")
}

iTEDB = {
    "888-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137_AfterReconnecting_gum_iTEDB-middle_D.2023_03_02_T.15_22_31_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW100.root","READ"),
    "888-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137_AfterReconnecting_gum_iTEDB-middle_D.2023_03_02_T.15_22_31_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW150.root","READ"),
    "888-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137_AfterReconnecting_gum_iTEDB-middle_D.2023_03_02_T.15_22_31_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW200.root","READ"),
    "888-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137_AfterReconnecting_gum_iTEDB-middle_D.2023_03_02_T.15_22_31_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW250.root","READ"),
    "88c-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDB-A2_D.2023_03_14_T.14_35_17_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "88c-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDB-A2_D.2023_03_14_T.14_35_17_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "88c-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDB-A2_D.2023_03_14_T.14_35_17_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "88c-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDB-A2_D.2023_03_14_T.14_35_17_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW250.root","READ"),
    "887-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDB-A2_D.2023_03_21_T.14_57_39_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "887-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDB-A2_D.2023_03_21_T.14_57_39_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "887-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDB-A2_D.2023_03_21_T.14_57_39_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "887-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDB-A2_D.2023_03_21_T.14_57_39_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW250.root","READ")
}

iTEDC = {
    "888-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_02_23_T.13_26_03_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW100.root","READ"),
    "888-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_02_23_T.13_26_03_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW150.root","READ"),
    "888-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_02_23_T.13_26_03_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW200.root","READ"),
    "888-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_02_23_T.13_26_03_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW250.root","READ"),
    "88c-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDC-A1_D.2023_03_14_T.14_41_53_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "88c-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDC-A1_D.2023_03_14_T.14_41_53_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "88c-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDC-A1_D.2023_03_14_T.14_41_53_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "88c-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDC-A1_D.2023_03_14_T.14_41_53_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW250.root","READ"),
    "887-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_03_21_T.15_05_52_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "887-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_03_21_T.15_05_52_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "887-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_03_21_T.15_05_52_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "887-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDC-A1_D.2023_03_21_T.15_05_52_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW250.root","READ")
}

iTEDD = {
    "888-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_02_23_T.13_03_18_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW100.root","READ"),
    "888-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_02_23_T.13_03_18_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW150.root","READ"),
    "888-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_02_23_T.13_03_18_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW200.root","READ"),
    "888-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_02_23_T.13_03_18_C.itedABCD_lab_2023.02.22_4.0v_888_300s_CW250.root","READ"),
    "88c-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDD-A1_D.2023_03_14_T.14_48_58_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "88c-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDD-A1_D.2023_03_14_T.14_48_58_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "88c-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDD-A1_D.2023_03_14_T.14_48_58_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "88c-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/CS137-iTEDD-A1_D.2023_03_14_T.14_48_58_C.itedABCD_lab_custom_2023.02.22_4.0v_887_300s_CW250.root","READ"),
    "887-100": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_03_21_T.15_12_02_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW100.root","READ"),
    "887-150": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_03_21_T.15_12_02_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW150.root","READ"),
    "887-200": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_03_21_T.15_12_02_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW200.root","READ"),
    "887-250": ROOT.TFile.Open("../../data/Multi_iTED_characterization/Cs137-iTEDD-A1_D.2023_03_21_T.15_12_02_C.itedABCD_lab_2023.02.22_4.0v_887_300s_CW250.root","READ")
}

for iTED in[0,1,2,3]:
    for Crystal in [0,1,2,3,4]:
        for Configuration in ["888", "887", "88c"]:
            for CW in [100,150,200,250]:
            
                spectra[
                    ["A","B","C","D"][iTED], Crystal
                ][
                    Configuration, CW
                ] = spectrum(
                    [iTEDA,iTEDB,iTEDC,iTEDD][iTED][f"{Configuration}-{CW}"].Get(
                        "{}_{}_amplitude_spectra;1".format(
                            "SCATTERER" if Crystal==0 else "ABSORBER",
                            ["A","B","C","D"][iTED] if Crystal==0 else "{}_{}".format(["A","B","C","D"][iTED],Crystal)
                        )
                    ), 
                    ["A","B","C","D"][iTED], 
                    Crystal, 
                    Configuration, 
                    CW, 
                    iTED_cal[:][["A","B","C","D"][iTED],Crystal]
                )

spectra.dropna(inplace=True)
spectra.applymap(str)

	iTED	A					B					C					D
	Crystal	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4
Configuration	Window
888	100	A.0.888.100	A.1.888.100	A.2.888.100	A.3.888.100	A.4.888.100	B.0.888.100	B.1.888.100	B.2.888.100	B.3.888.100	B.4.888.100	C.0.888.100	C.1.888.100	C.2.888.100	C.3.888.100	C.4.888.100	D.0.888.100	D.1.888.100	D.2.888.100	D.3.888.100	D.4.888.100
	150	A.0.888.150	A.1.888.150	A.2.888.150	A.3.888.150	A.4.888.150	B.0.888.150	B.1.888.150	B.2.888.150	B.3.888.150	B.4.888.150	C.0.888.150	C.1.888.150	C.2.888.150	C.3.888.150	C.4.888.150	D.0.888.150	D.1.888.150	D.2.888.150	D.3.888.150	D.4.888.150
	200	A.0.888.200	A.1.888.200	A.2.888.200	A.3.888.200	A.4.888.200	B.0.888.200	B.1.888.200	B.2.888.200	B.3.888.200	B.4.888.200	C.0.888.200	C.1.888.200	C.2.888.200	C.3.888.200	C.4.888.200	D.0.888.200	D.1.888.200	D.2.888.200	D.3.888.200	D.4.888.200
	250	A.0.888.250	A.1.888.250	A.2.888.250	A.3.888.250	A.4.888.250	B.0.888.250	B.1.888.250	B.2.888.250	B.3.888.250	B.4.888.250	C.0.888.250	C.1.888.250	C.2.888.250	C.3.888.250	C.4.888.250	D.0.888.250	D.1.888.250	D.2.888.250	D.3.888.250	D.4.888.250
887	100	A.0.887.100	A.1.887.100	A.2.887.100	A.3.887.100	A.4.887.100	B.0.887.100	B.1.887.100	B.2.887.100	B.3.887.100	B.4.887.100	C.0.887.100	C.1.887.100	C.2.887.100	C.3.887.100	C.4.887.100	D.0.887.100	D.1.887.100	D.2.887.100	D.3.887.100	D.4.887.100
	150	A.0.887.150	A.1.887.150	A.2.887.150	A.3.887.150	A.4.887.150	B.0.887.150	B.1.887.150	B.2.887.150	B.3.887.150	B.4.887.150	C.0.887.150	C.1.887.150	C.2.887.150	C.3.887.150	C.4.887.150	D.0.887.150	D.1.887.150	D.2.887.150	D.3.887.150	D.4.887.150
	200	A.0.887.200	A.1.887.200	A.2.887.200	A.3.887.200	A.4.887.200	B.0.887.200	B.1.887.200	B.2.887.200	B.3.887.200	B.4.887.200	C.0.887.200	C.1.887.200	C.2.887.200	C.3.887.200	C.4.887.200	D.0.887.200	D.1.887.200	D.2.887.200	D.3.887.200	D.4.887.200
	250	A.0.887.250	A.1.887.250	A.2.887.250	A.3.887.250	A.4.887.250	B.0.887.250	B.1.887.250	B.2.887.250	B.3.887.250	B.4.887.250	C.0.887.250	C.1.887.250	C.2.887.250	C.3.887.250	C.4.887.250	D.0.887.250	D.1.887.250	D.2.887.250	D.3.887.250	D.4.887.250
88c	100	A.0.88c.100	A.1.88c.100	A.2.88c.100	A.3.88c.100	A.4.88c.100	B.0.88c.100	B.1.88c.100	B.2.88c.100	B.3.88c.100	B.4.88c.100	C.0.88c.100	C.1.88c.100	C.2.88c.100	C.3.88c.100	C.4.88c.100	D.0.88c.100	D.1.88c.100	D.2.88c.100	D.3.88c.100	D.4.88c.100
	150	A.0.88c.150	A.1.88c.150	A.2.88c.150	A.3.88c.150	A.4.88c.150	B.0.88c.150	B.1.88c.150	B.2.88c.150	B.3.88c.150	B.4.88c.150	C.0.88c.150	C.1.88c.150	C.2.88c.150	C.3.88c.150	C.4.88c.150	D.0.88c.150	D.1.88c.150	D.2.88c.150	D.3.88c.150	D.4.88c.150
	200	A.0.88c.200	A.1.88c.200	A.2.88c.200	A.3.88c.200	A.4.88c.200	B.0.88c.200	B.1.88c.200	B.2.88c.200	B.3.88c.200	B.4.88c.200	C.0.88c.200	C.1.88c.200	C.2.88c.200	C.3.88c.200	C.4.88c.200	D.0.88c.200	D.1.88c.200	D.2.88c.200	D.3.88c.200	D.4.88c.200
	250	A.0.88c.250	A.1.88c.250	A.2.88c.250	A.3.88c.250	A.4.88c.250	B.0.88c.250	B.1.88c.250	B.2.88c.250	B.3.88c.250	B.4.88c.250	C.0.88c.250	C.1.88c.250	C.2.88c.250	C.3.88c.250	C.4.88c.250	D.0.88c.250	D.1.88c.250	D.2.88c.250	D.3.88c.250	D.4.88c.250

def get_resolution(cell):
    
    TH1D = cell.TH1D()
    
    TH1D.GetXaxis().SetRange(TH1D.FindBin(100),TH1D.FindBin(400))
    
    MaxBin   = TH1D.FindBin(TH1D.GetMaximumBin())
    
    ADC_Low  = MaxBin-60
    ADC_High = MaxBin+40

    gaussFit = ROOT.TF1("gaussFit", "pol1(0)+gaus(2)", ADC_Low, ADC_High)
    gaussFit.SetParameters(1000,-1,TH1D.GetMaximum(),MaxBin,10)
    TH1D.Fit(gaussFit,"QR")
    
    sigma = abs(gaussFit.GetParameter(4))
    centroid_ch = gaussFit.GetParameter(3)
    
    x1 = cell(centroid_ch+sigma*numpy.sqrt(2*numpy.log(2)))
    x2 = cell(centroid_ch-sigma*numpy.sqrt(2*numpy.log(2)))
    centroid = cell(centroid_ch)
        
    fwhm = x1-x2
            
    return sigma*numpy.sqrt(2*numpy.log(2))*2/centroid_ch*100, (fwhm/centroid)*100, centroid

def TH1D_draw(cell):
    
    TH1D = cell.TH1D()
    
    canvas = ROOT.TCanvas()
    canvas.cd()
    
    TH1D.SetTitle(repr(cell))
    TH1D.SetStats(False)
    
    latex = ROOT.TLatex()
    latex.SetNDC()
    latex.SetTextSize(0.03)
    
    TH1D.Draw("pe")
    
    l1,l2,l3 = get_resolution(cell)
    
    l4 = uproot.open(f"../../data/nTOF_March2022/888/CW100ns/Resolutions_Cs137_CenterScatter_iTED{cell.iTED()}_8.8.8_100ns.root:grResolEnergy;1").values()[1][cell.Crystal()]
    
    latex.DrawText(0.7, 0.8, "R_ch: {:.2f}%".format(l1))
    
    if l4*0.9 < l2 < l4*1.1:
        latex.DrawText(0.7, 0.75, "R_E: {:.2f}%".format(l2))
    else:
        latex.DrawText(0.7, 0.75, "->R_E: {:.2f}%".format(l2))
        
    if 662*(1-l2/100) < l3 < 662*(1+l2/100):
        latex.DrawText(0.7, 0.7, "E: {:.0f}keV".format(l3))
    else:
        latex.DrawText(0.7, 0.7, "->E: {:.0f}keV".format(l3))
        
    latex.DrawText(0.7, 0.65, "R_E(old): {:.2f}%".format(l4))
    latex.DrawText(0.7, 0.6, "Change: {:.2f}%".format(l2-l4))
            
    return canvas

Energy resolution @662keV

Using channel values

spectra.applymap(lambda x: get_resolution(x)[0]).T.describe().drop(['count', 'std'], axis=0).style.background_gradient(cmap ='YlOrRd',axis=None)

Configuration	888				887				88c
Window	100	150	200	250	100	150	200	250	100	150	200	250
mean	8.384339	8.284824	8.179738	8.088119	8.404514	8.260254	8.168116	8.069058	8.205656	8.095049	7.989033	7.893597
min	6.572851	6.511189	6.462154	6.437791	6.389740	6.388251	6.388026	6.387243	6.525593	6.523872	6.524571	6.523416
25%	7.075074	7.053681	7.008073	6.964889	7.078504	6.978950	6.931826	6.926262	7.019665	6.955688	6.916974	6.911327
50%	8.225909	8.070114	7.909846	7.781751	8.163990	7.992299	7.856192	7.710460	7.935067	7.823580	7.733675	7.599282
75%	9.645031	9.582242	9.465428	9.371003	9.864735	9.727948	9.630359	9.407380	9.262555	9.173130	9.039284	8.977927
max	11.434119	11.245839	10.762453	10.524706	11.490752	11.455784	11.441227	11.421454	10.867837	10.729804	10.612429	10.583095

Info in <TCanvas::MakeDefCanvas>:  created default TCanvas with name c1

Using the current calibration (March 2023, 888, 100ns)

spectra.applymap(lambda x: get_resolution(x)[1]).T.describe().drop(['count', 'std'], axis=0).style.background_gradient(cmap ='YlOrRd',axis=None)

Configuration	888				887				88c
Window	100	150	200	250	100	150	200	250	100	150	200	250
mean	7.193958	7.111687	7.024524	6.947401	7.098719	6.980382	6.905127	6.822373	7.027980	6.936768	6.848609	6.768283
min	5.690363	5.638254	5.596447	5.575697	5.567239	5.565940	5.565758	5.565070	5.678580	5.677089	5.677704	5.676694
25%	6.242677	6.203176	6.200747	6.188435	6.281600	6.245942	6.150291	6.113693	6.202920	6.187947	6.161628	6.147785
50%	6.982063	6.845986	6.713506	6.655423	6.821029	6.726619	6.615602	6.502844	6.768357	6.593864	6.543667	6.496192
75%	8.067847	7.972242	7.892667	7.716481	7.826232	7.692682	7.529721	7.397640	7.606198	7.504692	7.448275	7.348455
max	9.941246	9.793617	9.386924	9.029415	9.524203	9.044597	9.066551	8.877154	9.467014	9.299971	8.853431	8.514926

spectra.applymap(lambda x: get_resolution(x)[1]).style.background_gradient(cmap ='YlOrRd',axis=None)

	iTED	A					B					C					D
	Crystal	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4
Configuration	Window
888	100	6.993667	5.690363	8.003727	6.264532	8.513630	8.685116	7.545204	7.159496	6.921517	6.970458	9.941246	7.024431	5.801541	8.581080	8.260210	6.604624	6.177112	6.154822	6.158417	6.427960
	150	6.745153	5.638254	7.943185	6.214287	8.491202	8.421423	7.531137	7.111619	6.842958	6.928608	9.793617	6.849014	5.800469	8.484608	8.059413	6.501383	6.169841	6.125247	6.149794	6.432523
	200	6.659179	5.596447	7.917940	6.213641	8.473171	8.180773	7.442451	7.047676	6.765897	6.889133	9.386924	6.661115	5.802972	8.298828	7.884243	6.448186	6.162062	6.119100	6.145520	6.395222
	250	6.591387	5.575697	7.894197	6.200813	8.431370	8.083150	7.397516	6.999044	6.719459	6.856619	9.029415	6.493300	5.801645	8.054665	7.657242	6.372846	6.151302	6.100846	6.131791	6.405715
887	100	6.716906	5.885172	7.846681	6.556772	8.926923	8.910126	7.538841	6.771155	7.097204	6.870904	9.524203	6.960888	5.567239	8.476957	7.819416	6.328728	6.363272	5.773790	6.140214	5.898985
	150	6.535668	5.800937	7.777560	6.451929	8.902208	8.430194	7.412162	6.688939	7.037385	6.849367	9.044597	6.764300	5.565940	8.303461	7.664389	6.292431	6.348265	5.763566	6.106475	5.867876
	200	6.442909	5.771719	7.716941	6.419184	8.891864	8.231809	7.349736	6.622017	6.947128	6.741413	9.066551	6.609188	5.565758	8.082529	7.467314	6.171867	6.333189	5.742967	6.085562	5.842901
	250	6.400100	5.753039	7.708582	6.419219	8.877154	8.104824	7.293993	6.586469	6.829195	6.727379	8.635466	6.402065	5.565070	7.867197	7.206193	6.120226	6.323636	5.721918	6.094094	5.811644
88c	100	6.848400	6.095302	7.536584	6.269364	8.602156	8.331459	7.549031	6.688313	6.852857	6.632140	9.467014	7.046612	5.678580	8.494920	7.777696	6.421585	6.130319	5.779793	6.227103	6.130370
	150	6.623912	6.037643	7.482337	6.213026	8.631772	8.207789	7.438936	6.593293	6.594435	6.587102	9.299971	6.840054	5.677089	8.397128	7.571756	6.326870	6.111083	5.770381	6.218071	6.112710
	200	6.583704	6.009039	7.407379	6.181999	8.537732	7.989468	7.375075	6.536205	6.551128	6.534113	8.853431	6.661599	5.677704	8.144216	7.570963	6.219945	6.100512	5.753311	6.207167	6.077498
	250	6.509696	5.991072	7.388117	6.165802	8.514926	7.841426	7.285276	6.488878	6.432151	6.536032	8.405071	6.503505	5.676694	7.996617	7.335234	6.191500	6.093731	5.737227	6.195646	6.077063

Energy of the Cesium peak using the current calibration (March 2023, 888, 100ns)

spectra.applymap(lambda x: abs(get_resolution(x)[2]-662)/662*100).T.describe().drop(['count', 'std'], axis=0).style.background_gradient(cmap ='YlOrRd',axis=None)

Configuration	888				887				88c
Window	100	150	200	250	100	150	200	250	100	150	200	250
mean	2.783928	2.920516	3.030763	3.097189	1.955409	1.920312	1.916828	1.933787	2.357105	2.474974	2.551107	2.606813
min	0.261671	0.273354	0.137220	0.089146	0.029099	0.028333	0.134172	0.095745	0.070286	0.053619	0.043825	0.033794
25%	1.449584	1.852350	1.881064	1.917321	0.325375	0.655081	0.656098	0.700591	1.354216	1.346443	1.336762	1.389725
50%	2.920744	3.069998	3.110387	3.165389	1.821452	1.769053	1.586570	1.651227	2.083279	2.147551	2.184258	2.200536
75%	4.003028	4.287113	4.503136	4.566823	2.765623	2.633653	2.546075	2.561870	3.410597	3.651191	3.736920	3.937449
max	5.426153	5.436203	5.455493	5.461596	6.084582	6.018045	5.972706	5.965306	5.574989	5.593240	5.603651	5.625288

Noise using integral <200keV (Calibration: March 2023, 888, 100ns)

spectra.applymap(lambda x: x.Noise(300)).T.describe().drop(['count', 'std'], axis=0).style.background_gradient(cmap ='YlOrRd',axis=None)

Configuration	888				887				88c
Window	100	150	200	250	100	150	200	250	100	150	200	250
mean	81.683167	73.282833	67.859833	64.508500	80.962833	71.987167	66.279500	62.832000	77.353500	68.780667	63.268500	59.800333
min	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000
25%	53.284167	49.380000	47.319167	46.515833	54.305833	50.645000	47.484167	45.865000	52.565000	48.716667	45.085000	42.961667
50%	64.158333	63.945000	63.820000	63.720000	65.010000	64.695000	64.351667	64.263333	62.180000	61.200000	60.020000	59.376667
75%	111.253333	96.070000	91.945000	84.095000	103.073333	94.559167	87.672500	84.927500	98.923333	89.616667	82.640833	78.991667
max	192.766667	159.060000	136.826667	122.360000	208.850000	172.166667	147.503333	132.200000	197.046667	161.766667	138.343333	122.543333

spectra.applymap(lambda x: x.Noise(300)).style.background_gradient(cmap ='YlOrRd',axis=None)

	iTED	A					B					C					D
	Crystal	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4
Configuration	Window
888	100	90.290000	77.086667	52.390000	61.160000	0.000000	125.910000	0.000000	48.126667	52.656667	53.493333	192.766667	175.253333	66.003333	134.053333	115.713333	109.766667	95.040000	62.313333	61.446667	60.193333
	150	84.043333	71.373333	49.110000	60.306667	0.000000	110.973333	0.000000	42.986667	45.953333	49.470000	159.060000	147.933333	65.980000	109.503333	90.426667	106.370000	92.636667	61.910000	59.560000	58.060000
	200	79.276667	68.743333	47.593333	59.790000	0.000000	100.940000	0.000000	40.233333	41.723333	46.496667	136.826667	128.186667	65.963333	93.680000	75.560000	103.483333	91.366667	61.676667	58.580000	57.076667
	250	77.573333	67.570000	46.876667	59.330000	0.000000	95.043333	0.000000	38.550000	39.630000	45.433333	122.360000	114.976667	65.933333	81.836667	66.383333	101.693333	90.870000	61.506667	57.973333	56.630000
887	100	100.476667	73.836667	44.673333	64.903333	0.000000	105.963333	0.000000	59.993333	44.493333	47.973333	208.850000	178.473333	65.116667	138.773333	118.506667	91.030000	102.110000	60.210000	56.416667	57.456667
	150	96.436667	68.916667	41.740000	64.266667	0.000000	89.286667	0.000000	53.613333	34.890000	41.256667	172.166667	148.636667	65.123333	113.663333	93.933333	88.263333	98.593333	59.580000	54.323333	55.053333
	200	92.620000	66.403333	40.426667	63.606667	0.000000	78.896667	0.000000	49.836667	30.460000	37.726667	147.503333	128.506667	65.096667	97.070000	78.600000	86.023333	96.850000	59.163333	53.166667	53.633333
	250	90.830000	65.233333	39.680000	63.413333	0.000000	72.660000	0.000000	47.926667	28.590000	36.290000	132.200000	114.823333	65.113333	86.100000	68.856667	84.536667	95.800000	58.913333	52.660000	53.013333
88c	100	90.193333	65.680000	40.256667	59.766667	0.000000	105.183333	0.000000	58.153333	42.673333	44.520000	197.046667	171.106667	63.323333	132.530000	113.256667	91.996667	96.836667	61.036667	55.246667	58.263333
	150	85.250000	61.870000	37.690000	58.780000	0.000000	89.343333	0.000000	51.850000	34.940000	39.316667	161.766667	141.106667	63.286667	107.360000	90.006667	89.486667	93.453333	60.530000	53.203333	56.373333
	200	81.253333	59.863333	36.003333	58.193333	0.000000	78.560000	0.000000	47.910000	30.860000	36.610000	138.343333	121.696667	63.290000	91.240000	74.946667	86.803333	92.160000	60.176667	52.233333	55.226667
	250	78.733333	58.723333	35.386667	57.933333	0.000000	72.163333	0.000000	45.486667	29.060000	35.296667	122.543333	109.300000	63.276667	79.766667	65.703333	85.263333	90.980000	60.030000	51.596667	54.763333

Alpha activity using 1600keV < E < 2800keV (Calibration: March 2023, 888, 100ns)

spectra.applymap(lambda x: x.Alpha(300)).T.describe().drop(['count', 'std'], axis=0).style.background_gradient(cmap ='YlOrRd',axis=None)

Configuration	888				887				88c
Window	100	150	200	250	100	150	200	250	100	150	200	250
mean	151.097667	150.797667	150.653667	150.514000	154.837500	154.582500	154.394500	154.275000	152.493167	152.222833	151.983333	151.891667
min	23.603333	23.700000	23.723333	23.760000	23.936667	23.973333	24.003333	24.016667	24.230000	24.270000	24.380000	24.436667
25%	95.206667	95.145833	95.174167	95.186667	102.195000	102.238333	102.378333	102.337500	94.688333	94.653333	94.688333	94.721667
50%	176.700000	176.380000	176.303333	175.900000	181.468333	181.301667	181.325000	181.373333	175.650000	175.340000	175.136667	175.093333
75%	216.720833	216.290833	216.127500	216.008333	221.419167	220.749167	220.326667	220.070000	221.795000	221.416667	220.708333	220.585000
max	238.063333	238.066667	238.070000	238.070000	238.666667	238.663333	238.666667	238.666667	240.580000	240.583333	240.583333	240.583333

spectra.applymap(lambda x: x.Alpha(300)).style.background_gradient(cmap ='YlOrRd',axis=None)

	iTED	A					B					C					D
	Crystal	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4	0	1	2	3	4
Configuration	Window
888	100	24.860000	148.353333	114.170000	36.073333	31.263333	144.330000	121.743333	209.013333	203.166667	216.080000	150.233333	230.230000	238.063333	218.643333	228.553333	23.603333	222.950000	38.316667	206.363333	215.943333
	150	24.983333	148.320000	114.080000	36.083333	31.283333	143.596667	120.430000	208.673333	202.793333	215.690000	149.966667	229.516667	238.066667	217.843333	227.483333	23.700000	222.893333	38.343333	206.433333	215.773333
	200	25.220000	148.370000	114.116667	36.090000	31.333333	143.350000	119.413333	208.500000	202.830000	215.753333	149.776667	229.026667	238.070000	216.970000	227.050000	23.723333	222.910000	38.346667	206.376667	215.846667
	250	25.290000	148.366667	114.143333	36.110000	31.343333	143.176667	118.800000	208.363333	202.626667	215.776667	149.173333	228.880000	238.070000	216.573333	226.470000	23.760000	222.850000	38.316667	206.370000	215.820000
887	100	24.356667	153.090000	122.986667	36.220000	30.953333	152.093333	134.123333	212.510000	209.846667	222.486667	152.493333	232.793333	238.666667	221.063333	231.833333	23.936667	225.200000	39.820000	213.570000	218.706667
	150	24.453333	153.113333	123.040000	36.230000	31.023333	152.030000	131.930000	212.270000	209.490000	222.096667	152.710000	232.123333	238.663333	220.300000	231.030000	23.973333	225.110000	39.833333	213.546667	218.683333
	200	24.610000	153.103333	123.233333	36.260000	31.046667	151.953333	130.370000	212.096667	209.546667	222.146667	152.266667	231.810000	238.666667	219.720000	230.076667	24.003333	224.970000	39.813333	213.556667	218.640000
	250	24.713333	153.210000	123.183333	36.233333	31.053333	151.973333	129.570000	211.876667	209.536667	222.030000	151.726667	231.156667	238.666667	219.416667	230.063333	24.016667	224.990000	39.800000	213.550000	218.733333
88c	100	24.230000	144.443333	113.343333	34.836667	31.183333	147.626667	123.030000	206.073333	200.206667	218.760000	151.093333	232.263333	240.580000	220.146667	228.853333	24.933333	227.563333	38.723333	215.233333	226.740000
	150	24.270000	144.353333	113.293333	34.786667	31.203333	147.060000	121.280000	205.773333	199.803333	218.590000	150.876667	231.760000	240.583333	219.680000	227.953333	25.010000	227.630000	38.733333	215.190000	226.626667
	200	24.380000	144.273333	113.340000	34.780000	31.230000	146.900000	119.803333	205.500000	199.890000	218.460000	150.383333	231.193333	240.583333	218.746667	227.136667	25.050000	227.530000	38.733333	215.160000	226.593333
	250	24.436667	144.393333	113.380000	34.766667	31.270000	146.443333	118.963333	205.386667	199.816667	218.576667	150.370000	230.890000	240.583333	218.523333	226.910000	25.093333	227.546667	38.746667	215.126667	226.610000

Draw fits

canvas = spectra.applymap(TH1D_draw)
#canvas.applymap(lambda x: type(x).__name__)

for col in canvas.columns:
    for row in canvas.index:
        canvas.loc[row,col].Draw()

Conclusions: